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Efficient Methods for Filtering and Ranking Fragments for the Prediction of Structurally Variable Regions in Proteins by Philipp Heuser; Gerd Wohlfahrt; Dietmar Schomburg is a Biochemistry, Genetics and Molecular Biology article available to read on EtoBox.

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## Abstract The prediction of protein 3D structures close to insertions and deletions or, more generally, loop prediction, is still one of the major challenges in homology modeling projects. In this article, we developed ranking criteria and selection filters to improve knowledge‐based loop predictions. These criteria were developed and optimized for a test data set containing 678 insertions and deletions. The examples are, in principle, predictable from the used loop database with an RMSD < 1 Å and represent realistic modeling situations. Four noncorrelated criteria for the selection of fragments are evaluated. A fast prefilter compares the distance between the anchor groups in the template protein with the stems of the fragments. The RMSD of the anchor groups is used for fitting and ranking of the selected loop candidates. After fitting, repulsive close contacts of loop candidates with the template protein are used for filtering, and fragments with backbone torsion angles, which are unfavorable according to a knowledge‐based potential, are eliminated. By the combined application of these filter criteria to the test set, it was possible to increase the percentage of predictions wi

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Author

Philipp Heuser; Gerd Wohlfahrt; Dietmar Schomburg

Publisher

John Wiley and Sons; Wiley (John Wiley & Sons); Wiley-Liss Inc; Wiley (ISSN 0887-3585)

Published

2003

Language

EN

Field

Biochemistry, Genetics and Molecular Biology (Life Sciences)